September 29, 2016  |  Announcements, Cytobank, User Stories  |  By  |  0 Comments

Customer Story: Reema Baskar, Stanford Medicine

Welcome to Cytobank User Stories, a series featuring interviews with Cytobank users on their research, scientific vision, and use of fluorescence and mass cytometry.

This week we interview Reema Baskar, a graduate student in the Cancer Biology Department at Stanford University, co-mentored by Sean Bendall and Sylvia Plevritis. We asked Reema about how she uses Cytobank’s high-dimensional tools to help elucidate mechanisms of drug resistance in cancer, and her early experience beta-testing our new CITRUS implementation.

What is an important problem in human health and/or fundamental biology that you’d like to address? What is your scientific vision?
Reema Baskar
Cancer Biology Dept.
Stanford University

My vision is to develop high-dimensional techniques and computational tools to address the challenge of ‘big data.’ My hope is that these tools may be broadly applied to aid our understanding of the human condition. Technology, such as mass cytometry (CyTOF), has made it possible to capture different facets of biology such as cell function, epigenetic traits, and transcriptional readouts with infinitesimal single-cell granularity.

What do you study?
As a graduate student within the Cancer Biology department, my focus has been to investigate drug resistance in cancer. The way we are addressing this problem is by looking at epigenetic traits, phenotypic markers, and functional readouts within healthy and disease populations. We need to characterize healthy variation to thoroughly understand how these features are dysregulated in disease.
What’s your favorite Cytobank feature?
I like that Cytobank is user-friendly. The interface provides me with an efficient method for viewing data and performing quality checks before exporting statistics and files for additional downstream analyses.
What do you like about the new Cytobank CITRUS implementation? How will you use this tool to improve your analysis moving forward in your research?
Like other Cytobank implementations, CITRUS is easy to use. The interface doesn’t require a computational background to apply the tool. I plan on using CITRUS to predict which features or cell subsets distinguish drug resistant vs. drug sensitive patients.
What are some of your favorite papers?
From Sui Huang’s group:


What do you do for fun?
I have a dance background and love dancing. I like mixing music, and play gigs sometimes. I also work as an events coordinator and throw parties for Stanford grad students. It’s pretty fun with my music and bartending skills!